但是模型建立起来后，几乎不可避免地把贝叶斯的预先假定理论也纳入了模型中。
It appears to be objective. But when models are built, it is almost impossible to avoid including Bayesian-style prior assumptions in them.
贝叶斯方法是那些明确地在分类和回归问题中应用贝叶斯定理的算法。
Bayesian methods are those that are explicitly apply Bayes' Theorem for problems such as classification and regression.
通过分析贝叶斯定理的变形公式和属性相关性度量，提出一种基于强属性限定的贝叶斯分类模型SANBC。
On the basis of analyzing a variant of Bayes theorem and the evaluation of condition attribute with correlation, SANBC is proposed.
但是模型建立起来后，几乎不可避免地把贝叶斯的预先假定理论也纳入了模型中。
But when models are built it is almost impossible to avoid including Bayesian-style prior assumptions in them.
但是模型建立起来后，几乎不可避免地把贝叶斯的预先假定理论也纳入了模型中。
But when models are built it is almost impossible to avoid including Bayesian-style prior assumptions in them.
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